The analysis of genetic and biological data is an active area of research that continually undergoes substantial changes. It is important that new methodologies are appropriately evaluated so that the best available methods and approaches can be applied to data. This requires the knowledge and experience of skilled statistical geneticists, biostatisticians, programmers and systems administrators. The Data Analysis and Bioinformatics Core (DABC) will provide such a team with a proven collaborative research record. The DABC will promote and facilitate the research undertaken by the Oklahoma Sjogren's Syndrome Center of Research Translation (OSSCORT) Project and Pilot Investigators, as well as the Administrative and Clinical Cores and will provide project-specific experimental design and statistical methods necessary for each project to accomplish their major goals. In an effort to assist all OSSCORT Projects and Cores, the DABC will be an integral part of the research team in study development, implementing high quality data management, providing state of the art analysis, and providing high level informatics and programming capabilities. Centralized analysis through the DABC will enable standardization of statistical diagnostic checks of distributional assumptions, outliers (overly influential data points), colinearity, etc., ensuring that all analyses are of the same high quality and rigor. The DABC will provide efficient management of data shared between projects, better quality control of both data and analysis and overall assessment of OSSCORT progress. Specifically, our goals are to: 1) collaborate with investigators to outline the most appropriate and powerful study design, perform data cleaning and statistical analyses, interpret analyses, and assist with the preparation of publications, presentations and progress reports;2) provide secure, standardized and easily accessible data storage and management for all data collected as a part of the OSSCORT Projects and Cores;3) synthesize data across projects through sophisticated modeling approaches and 4) develop, modify and/or apply novel statistical analysis methods to the appropriate hypotheses.